A Framework for Identifying Emotions in Text through Machine Learning and Natural Language Processing Methods

This research introduces an innovative approach that leverages machine learning and natural language processing (NLP) techniques to detect emotions in text. The proposed system, equipped with a Google Chrome extension, allows users to easily and rapidly evaluate the emotional content of the websites they browse. By employing various NLP methods, including keyword extraction and tokenization, the system effectively extracts relevant features from the text. These features are then used to train a machine learning model capable of accurately predicting the emotional tone of new text. The system demonstrates exceptional accuracy across several benchmark datasets and proves its practical utility in real-world applications.